Author: Advanced AI Bot

IBL News | New York Paris–based Mistral AI unveiled Mistral Small 3.1, a new multimodal open-source model. According to the company, it is “the best model in its weight class ” and “outperforms comparable models like Gemma 3 and GPT-4o Mini. “ Released under an Apache 2.0 license, Mistral Small 3.1 has an expanded context window of up to 128k tokens and a delivery inference speed of 150 tokens per second. Experts say that Mistral Small 3 is competitive with larger models such as Llama 3.3 70B or Qwen 32B and replaces opaque proprietary models like GPT4o-mini. Mistral Small 3 can be fine-tuned…

A DeepSeek moment is playing out in China’s vast countryside, as rural residents discover that chatbots are useful for providing advice on topics ranging from pig farming to pest control.Thanks to China’s extensive internet coverage and mobile phone penetration, the country’s rural residents, who account for a third of its 1.4 billion population, are eager to apply artificial intelligence (AI) services in farming and rural life after DeepSeek, the Hangzhou-based start-up, triggered a nationwide frenzy of AI adoption with its open-source models.Chinese Big Tech firms, such as Alibaba Group Holding and Tencent Holdings, have in turn developed easy-to-use chatbots to…

Alibaba Group (NYSE: BABA, HK:9988) surged in investor interest after Mizuho raised its price target on the Chinese tech giant’s U.S.-listed shares from $140 to $170, maintaining an “Outperform” rating. The bullish update positions Alibaba as one of Mizuho’s top picks among Asian internet stocks, driven largely by the company’s aggressive expansion into artificial intelligence. Mizuho’s analysts highlighted Alibaba’s clear AI product roadmap and strong foundational tech, which includes the advanced Qwen model. According to the report, Qwen is already on par—or even ahead—of major global AI models, and is integrated across a wide range of Alibaba’s development tools, enhancing…

(MENAFN- PR Newswire) The launch of ERNIE 4.5 and ERNIE X1 marks a significant milestone in pushing the boundaries of multimodal and reasoning models, offering advanced capabilities at a more accessible price point. It also underscores Baidu’s commitment to continued investment in developing smarter and more powerful next-generation foundation models. Baidu also plans to progressively integrate both ERNIE 4.5 and X1 into its product ecosystem. This integration will include Baidu Search, the Wenxiaoyan app, and other offerings, delivering a more versatile and enhanced experience to a broader base of individual users. With the addition of ERNIE 4.5 and ERNIE X1…

AI tools are proving useful across a range of applications, from helping to drive the new era of business transformation to helping artists craft songs. But which applications are providing the most value to users? We’ll dig into that question in a series of blog posts that introduce the Semantic Telemetry project at Microsoft Research. In this initial post, we will introduce a new data science approach that we will use to analyze topics and task complexity of Copilot in Bing usage. Human-AI interactions can be iterative and complex, requiring a new data science approach to understand user behavior to…

Humans excel at processing vast arrays of visual information, a skill that is crucial for achieving artificial general intelligence (AGI). Over the decades, AI researchers have developed Visual Question Answering (VQA) systems to interpret scenes within single images and answer related questions. While recent advancements in foundation models have significantly closed the gap between human and machine visual processing, conventional VQA has been restricted to reason about only single images at a time rather than whole collections of visual data. This limitation poses challenges in more complex scenarios. Take, for example, the challenges of discerning patterns in collections of medical…

We recently surveyed nearly 700 AI practitioners and leaders worldwide to uncover the biggest hurdles AI teams face today. What emerged was a troubling pattern: nearly half (45%) of respondents lack confidence in their AI models. Despite heavy investments in infrastructure, many teams are forced to rely on tools that fail to provide the observability and monitoring needed to ensure reliable, accurate results. This gap leaves too many organizations unable to safely scale their AI or realize its full value.  This isn’t just a technical hurdle – it’s also a business one. Growing risks, tighter regulations, and stalled AI efforts…

MongoDB Inc. finally delivered a quarterly profit as it posted its fiscal 2025 fourth-quarter results, crushing the Street’s targets on earnings and revenue. However, its outlook for the new fiscal year was a big disappointment, sending investors running for the hills as the value of its stock plummeted in late trading. The company reported earnings before certain costs such as stock compensation of $1.28 per share on revenue of $548.4 million, up 20% from the same period one year ago. They were impressive numbers that far surpassed expectations, with analysts targeting earnings of just 60 cents per share on sales…

Image: seventyfourimages/Envato Elements AlexNet, which was released in 2012, is widely credited with sparking the modern AI revolution, particularly in the field of computer vision. Last week, the Computer History Museum in collaboration with Google made the source code for AlexNet publicly available on GitHub; this move gives researchers, developers, and AI enthusiasts a chance to dive into the foundational code that helped shape today’s AI landscape. What is AlexNet, and why does it matter? AlexNet was the deep-learning model that proved neural networks could significantly outperform traditional image recognition methods. Developed by Alex Krizhevsky, Ilya Sutskever, and their advisor…

From deal activity to top investors, we analyze the shifting landscape for AI in clinical trials to determine how the tech is transforming drug development for the better. This is the third and final report in a 3-part series on how AI is reshaping discovery, preclinical, and clinical research in drug R&D. Read part 1 on the discovery phase and part 2 on preclinical development. Clinical development represents one of pharma’s costliest and riskiest investments. Trials average $55M each, per a study in JAMA Health Forum, and can take more than a decade to complete. However, over 90% of drugs…